Projects

Building methods, teams, and capabilities.

Examples of research leadership, organization building, and the application of data science to business decisions.

Building Core Data Science at DiDi

Established the team, defined its mandate and research priorities, and supported scientific evaluation across more than 10 business lines.

From Statistical Research to Experimentation Capabilities

Led CUPED and rerandomization research and platform adoption, connecting statistical foundations with product design and validation.

Scaling Marketplace Data Science

Grew the team from 7 to 22 people, supporting marketplace strategy, technology, and pricing.

Further areas of work

Statistical Foundations for LLM Evaluation — Aligning evaluation objectives, sampling designs, and inference; developing evaluator reliability standards.

Growth Measurement and Investment Decisions — Campaign evaluation, attribution, lifetime value, and budgeting models.

Data Products for Operations — Fulfillment metrics and data products supporting delivery and inventory decisions.